Object detection refers to the problem of identifying the existence of objects of certain classes and find bounding boxes for them in single images. Object detection in the past decade was mainly based on the use of SIFT and HOG features. Although researchers have developed algorithms that demonstrated good performance for single class object detection (e.g. pedestrians), the multi-class object detection problem remains difficult. In particular, prior to 2012, the state-of-the-art method (deformable part models) achieved 33.4% accuracy on the PASCAL VOC 2010 dataset [1]}, which contains 20 object classes.
